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Objective Aiming at the problems of lacking initiative in upper limb rehabilitation training equipment, single training mode, and low active participation of patients, an upper limb continuous motion estimation algorithm model based on multi-modal information fusion was proposed, so to realize accurate estimation of elbow joint torque. Methods Firstly, the surface electromyography (sEMG) signal and posture signal of participants were collected at four angular velocities, and the time domain characteristics of the signal were extracted. The principal component analysis was adopted to multi-feature fusion. The back propagation neural network (BPNN) was optimized through the additional momentum and the adaptive learning rate method. The particle swarm optimization (PSO) algorithm was used to optimize the neural network and a continuous motion estimation model based on PSO-BPNN was constructed. Finally, the joint torque calculated by the second type of Lagrangian equation was used as the accurate value to train the model. The performance of the model was compared with the traditional BP neural network model. Results The root mean square error (RMSE) of the traditional BP neural network model was 558.9 N·m, and the R2 coefficient was 77.19%, Whereas the RMSE and the R2 coefficient of the optimized model were 113.6 mN·m and 99.12%, respectively.Thereby, the accuracy of torque estimation was improved apparently. Conclusions The method for continuous motion estimation of the elbow joint proposed in this study can estimate the motion intention accurately, and provide a practical scheme for the active control of upper exoskeleton rehabilitation robot.
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ObjectiveTo present a method for evaluating the gait symmetry of microprocessor-controlled prosthetic knee (MPK). MethodsA kind of proto-MPK, AiKneeOne, and a wearable gait collect system, were made. The phases of the first double-limb support, the single-limb support, the second double-limb support, and the swing were used to calculate symmetry index (SI), ratio Ⅰ (RI) and ratio II (RII). Five heathy persons walked on the treadmill wearing AiKneeOne at speeds of 0.5, 0.7, 1.1 m/s, and the indice were collected with the wearable gait collect system. ResultsUnder different velocities, The absolute value of SI and RII were very little and the RI were close to one at the phases of the first double-limb support and the second double-limb support, but they were not very satisfactory in the phases of the single-limb support and the swing. ConclusionThe developed MPK AiKneeOne is potential to reconstruct the gait of amputees, and the gait symmetry indice can be used to evaluate the wearing performance of MPK.
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ObjectiveAiming at the need of control strategy switching of intelligent above-knee prosthetic, taking the plantar pressure of human walking as the research object, and based on fuzzy logic algorithm, a gait phase division method based on plantar pressure of prosthetic is proposed. MethodsThree flexible force sensors installed on the soles of the false feet were used to collect the plantar pressure information of the test object under three different walking modes (walking on the flat road, walking downhill and walking down the stairs). After data fusion processing, it was sent to the fuzzy logic controller, and the recognition results were output according to the IF-THEN rule, the scale and sensitivity factor. ResultsThrough the testing of five healthy people as substitute, the results showed that the accuracy of gait phase recognition for walking on the flat road, walking down the stairs and walking downhill were (95.3±2.4)%, (81.5±6.3)% and (90.7±3.5)%, respectively. ConclusionThe accuracy of recognition basically meets the requirements in this project. This method can be applied in the gait phase recognition of intelligent above-knee prosthetic.
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Objective To analyze and assess the postoperative motor function in children with spastic cerebral palsy (SCP) by surface electromyography (sEMG) and joint angle. Methods Sixteen children with SCP were involved in this study. The sEMG of rectus femoris, biceps femoris, semitendinosus, tibialis anterior, lateral gastrocnemius and medial gastrocnemius muscles and joint angles of the hip, knee and ankle during straight walking were collected preoperatively and postoperatively. In every gait phase, the mean values of joint angles, root mean square and integrated electromyography of sEMG were calculated, to evaluate muscle strength and muscular tension quantitatively. Results The muscle tension of lower limbs was significantly decreased (P<0.05). The muscle strength of rectus femoris and biceps femoris was decreased in the swing phase. At the midswing and terminal swing phase, the strength of tibialis anterior increased significantly (P<0.05). The flexion angle of hip and knee decreased significantly (P<0.05). The dorsiflexion angle of ankle increased significantly (P<0.05), and the varus angle decreased significantly (P<0.05). Conclusions After operation, the crouching gait and clubfoot were improved positively. Therefore, the motor function of children was improved. Combining sEMG and joint angle can evaluate the muscle function of patients quantitatively, and it also can provide references for clinical diagnosis.
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At present, the upper limb function of stroke patients is often assessed clinically using a scale method, but this method has problems such as time-consuming, poor consistency of assessment results, and high participation of rehabilitation physicians. To overcome the shortcomings of the scale method, intelligent upper limb function assessment systems combining sensors and machine learning algorithms have become one of the hot research topics in recent years. Firstly, the commonly used clinical upper limb functional assessment methods are analyzed and summarized. Then the researches on intelligent assessment systems in recent years are reviewed, focusing on the technologies used in the data acquisition and data processing parts of intelligent assessment systems and their advantages and disadvantages. Lastly, the current challenges and future development directions of intelligent assessment systems are discussed. This review is hoped to provide valuable reference information for researchers in related fields.
Subject(s)
Humans , Algorithms , Physical Therapy Modalities , Stroke/diagnosis , Stroke Rehabilitation , Upper ExtremityABSTRACT
Objective To analyze the gait characteristics of hip disarticulation amputees, and analyze the reasons for their differences from normal gait, so as to assist clinical diagnosis and evaluation. Methods Through the portable human motion capture device and plantar pressure analysis system, the kinematics and plantar pressure information of 5 hip amputees were collected and compared with 15 healthy volunteers in control group. Gait differences between the amputees and normal subjects and between the affected leg side and the healthy leg side of the amputees were compared. Results The proportion of double-support period for hip amuptees was higher than that of normal gait. Step length, step time, loading response period, mid support period, pre-swing period, proportion of the swing period for the affected leg side and healthy leg side of hip amputees showed significant differences with those of control group. The relative symmetry index of the gait for hip amputees was 0.60±0.05. Compared with the affected leg side, the support period of the healthy leg side was extended, the step length was shortened, the ground reaction force was greater than that of the affected leg side, and the center of pressure trajectory shifted to the affected leg side. Conclusions The gait of hip amputees is significantly different from that of normal people. Hip amputees have weak walking ability, poor gait symmetry, and they lack of continuity in the body’s center of gravity. The results provide experimental basis and theoretical analysis for the design of mechanical structure and control system of novel hip prosthesis.
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The body weight support rehabilitation training system has now become an important treatment method for the rehabilitation of lower limb motor dysfunction. In this paper, a pelvic brace body weight support rehabilitation system is proposed, which follows the center of mass height (CoMH) of the human body. It aims to address the problems that the existing pelvic brace body weight support rehabilitation system with constant impedance provides a fixed motion trajectory for the pelvic mechanism during the rehabilitation training and that the patients have low participation in rehabilitation training. The system collectes human lower limb motion information through inertial measurement unit and predicts CoMH through artificial neural network to realize the tracking control of pelvic brace height. The proposed CoMH model was tested through rehabilitation training of hemiplegic patients. The results showed that the range of motion of the hip and knee joints on the affected side of the patient was improved by 25.0% and 31.4%, respectively, and the ratio of swing phase to support phase on the affected side was closer to that of the gait phase on the healthy side, as opposed to the traditional body weight support rehabilitation training model with fixed motion trajectory of pelvic brace. The motion trajectory of the pelvic brace in CoMH mode depends on the current state of the trainer so as to realize the walking training guided by active movement on the healthy side of hemiplegia patients. The strategy of dynamically adjustment of body weight support is more helpful to improve the efficiency of walking rehabilitation training.
Subject(s)
Humans , Biomechanical Phenomena , Gait , Hemiplegia , Pelvis , Range of Motion, Articular , Stroke Rehabilitation , WalkingABSTRACT
The rotation center of traditional hip disarticulation prosthesis is often placed in the front and lower part of the socket, which is asymmetric with the rotation center of the healthy hip joint, resulting in poor symmetry between the prosthesis movement and the healthy lower limb movement. Besides, most of the prosthesis are passive joints, which need to rely on the amputee's compensatory hip lifting movement to realize the prosthesis movement, and the same walking movement needs to consume 2-3 times of energy compared with normal people. This paper presents a dynamic hip disarticulation prosthesis (HDPs) based on remote center of mechanism (RCM). Using the double parallelogram design method, taking the minimum size of the mechanism as the objective, the genetic algorithm was used to optimize the size, and the rotation center of the prosthesis was symmetrical with the rotation center of the healthy lower limb. By analyzing the relationship between the torque and angle of hip joint in the process of human walking, the control system mirrored the motion parameters of the lower on the healthy side, and used the parallel drive system to provide assistance for the prosthesis. Based on the established virtual prototype simulation platform of solid works and Adams, the motion simulation of hip disarticulation prosthesis was carried out and the change curve was obtained. Through quantitative comparison with healthy lower limb and traditional prosthesis, the scientificity of the design scheme was analyzed. The results show that the design can achieve the desired effect, and the design scheme is feasible.
Subject(s)
Humans , Arthroplasty, Replacement, Hip , Artificial Limbs , Biomechanical Phenomena , Hip Joint , Hip Prosthesis , Prosthesis Design , Range of Motion, Articular , WalkingABSTRACT
Objective To study mechanical properties of the interface between hip residual limb and hip socket during the stance phase by using the finite element analysis (FEA) method, so as to provide the theoretical basis for structure optimization and design of hip socket, as well as the research basis for comfort evaluation of hip socket. Methods According to CT scan images of the patient’s residual limb, the model of bone, soft tissues and socket was reconstructed by reverse modeling. The distribution of normal stress and shear stress on the interface between hip residual limb and hip socket was analyzed and a pressure acquisition module system was designed to verify the stress distribution condition. Results The interfacial stress between hip residual limb and hip socket was mainly distributed in the waist and the bottom of the residual limb, and the interfacial stress was more evenly distributed in the rest of the residual limb. The results of finite element calculation were in good agreement with the system measurement results of pressure acquisition module. Conclusions In order to improve force transfer and safety and comfort of the hip socket, it is necessary to fully consider stress condition of the waist and bottom of the residual limb, as well as the coordination degree between residual limb and hip socket.
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A software and hardware platform for gait simulation and system evaluation for lower limb intelligent prosthesis is proposed and designed, in order that the wearable symmetry effect of the intelligent knee prosthesis can be quantitatively analyzed by machine test instead of human wear test. The whole-body three-dimensional gait and motion analysis system instrument, a device to collect gait data such as joint angle and stride of adults, was used for extracting simulated gait characteristic curve. Then, the gait curve was fitted based on the corresponding joint to verify the feasibility of the test platform in the experiment. Finally, the developed artificial knee prosthesis was worn on the prosthetic evaluation system to quantitatively analyze the gait symmetry effect. The results showed that there was no significant difference in gait symmetry between the developed knee joints at different speeds, which could reach more than 88%. The simulation and evaluation of the prosthetic gait have good effects on the functional simulation and evaluation of the lower limb intelligent prosthesis.
Subject(s)
Adult , Humans , Artificial Limbs , Biomechanical Phenomena , Gait , Knee Joint , Knee Prosthesis , Prosthesis DesignABSTRACT
The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically.
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Humans , Electroencephalography , Electromyography , Motor Cortex , Physiology , Muscle, Skeletal , Physiology , ResearchABSTRACT
@#Objective To carry out a research of terrain recognition on intelligent knee joint from the perspective of pure visual information.Methods The whole experimental environment was illuminated by halogen lamp, which made the brightness and color temperature of the set scene change less. The machine vision module was embedded in the intelligent knee joint control system. The road image data was collected by the camera in real time, and the captured image was processed in grayscale. The normalized cross correlation algorithm (NCC) was used to match the image pattern to identify the corresponding road conditions.Results The accuracy rates of the road vision, up/down hill, and up/down stairs recognized by the machine vision module were 88.6%, 85.3%, 78.4%, 87.5%, and 77.9%, respectively. The recognition effect was good, and the recognition time was within one second, real-time performance was strong.Conclusion The effectiveness and feasibility of intelligent knee joint prosthetic road condition recognition based on pure visual information is proved.
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With the aging of the society, the number of stroke patients has been increasing year by year. Compared with the traditional rehabilitation therapy, the application of upper limb rehabilitation robot has higher efficiency and better rehabilitation effect, and has become an important development direction in the field of rehabilitation. In view of the current development status and the deficiency of upper limb rehabilitation robot system, combined with the development trend of all kinds of products of the upper limb rehabilitation robot, this paper designed a center-driven upper limb rehabilitation training robot for cable transmission which can help the patients complete 6 degrees of freedom (3 are driven, 3 are underactuated) training. Combined the structure of robot with more joints rehabilitation training, the paper choosed a cubic polynomial trajectory planning method in the joint space planning to design two trajectories of eating and lifting arm. According to the trajectory equation, the movement trajectory of each joint of the robot was drawn in MATLAB. It laid a foundation for scientific and effective rehabilitation training. Finally, the experimental prototype is built, and the mechanical structure and design trajectories are verified.
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Rapid and accurate recognition of human action and road condition is a foundation and precondition of implementing self-control of intelligent prosthesis. In this paper, a Gaussian mixture model and hidden Markov model are used to recognize the road condition and human motion modes based on the inertial sensor in artificial limb (lower limb). Firstly, the inertial sensor is used to collect the acceleration, angle and angular velocity signals in the direction of , and axes of lower limbs. Then we intercept the signal segment with the time window and eliminate the noise by wavelet packet transform, and the fast Fourier transform is used to extract the features of motion. Then the principal component analysis (PCA) is carried out to remove redundant information of the features. Finally, Gaussian mixture model and hidden Markov model are used to identify the human motion modes and road condition. The experimental results show that the recognition rate of routine movement (walking, running, riding, uphill, downhill, up stairs and down stairs) is 96.25%, 92.5%, 96.25%, 91.25%, 93.75%, 88.75% and 90% respectively. Compared with the support vector machine (SVM) method, the results show that the recognition rate of our proposed method is obviously higher, and it can provide a new way for the monitoring and control of the intelligent prosthesis in the future.
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The performance of intelligent prosthetic knee has an important effect on the realization of physiological gait of transfemoral amputees. A new type of single axis hydraulic damping knee prosthesis was designed based on the analysis of physiological gait. The training methods of the stance and swing phase were proposed. Knee prosthesis test was done through simulation and measurement device. The control target of peak flexion angle during swing of knee prosthesis is chosen to be 60-70°. When the damper valve closure was 0%, maximum swing-phase knee flexion angle of knee prosthesis were (86±2)°, (91±3)° and (97±3)° with the speed of 0.8 m/s, 1.2 m/s and 1.8 m/s, respectively. Once the valve closure was changed, maximum swing-phase knee flexion angle with different speeds could be adjusted between 60° and 70° and the required valve closure percentage were separately 25%, 40% and 70%. The damping adjustment law of intelligent knee prosthesis to achieve physiological gait was revealed.
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Based on the structure and motion bionic principle of the normal adult fingers, biological characteristics of human hands were analyzed, and a wearable exoskeleton hand function training device for the rehabilitation of stroke patients or patients with hand trauma was designed. This device includes the exoskeleton mechanical structure and the electromyography (EMG) control system. With adjustable mechanism, the device was capable to fit different finger lengths, and by capturing the EMG of the users' contralateral limb, the motion state of the exoskeleton hand was controlled. Then driven by the device, the user's fingers conducting adduction/abduction rehabilitation training was carried out. Finally, the mechanical properties and training effect of the exoskeleton hand were verified through mechanism simulation and the experiments on the experimental prototype of the wearable exoskeleton hand function training device.
Subject(s)
Humans , Bionics , Electromyography , Exoskeleton Device , Fingers , Hand , Motion , Stroke RehabilitationABSTRACT
The number of people with physical disabilities is increasing year by year, and the trend of population aging is more and more serious. In order to improve the quality of the life, a control system of accessible home environment for the patients with serious disabilities was developed to control the home electrical devices with the voice of the patients. The control system includes a central control platform, a speech recognition module, a terminal operation module, etc. The system combines the speech recognition control technology and wireless information transmission technology with the embedded mobile computing technology, and interconnects the lamp, electronic locks, alarms, TV and other electrical devices in the home environment as a whole system through a wireless network node. The experimental results showed that speech recognition success rate was more than 84% in the home environment.
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Humans , Computers , Disabled Persons , Speech Recognition Software , Wireless TechnologyABSTRACT
The present paper proposed a central-driven structure of upper limb rehabilitation robot in order to reduce the volume of the robotic arm in the structure, and also to reduce the influence of motor noise, radiation and other adverse factors on upper limb dysfunction patient. The forward and inverse kinematics equations have been obtained with using the Denavit-Hartenberg (D-H) parameter method. The motion simulation has been done to obtain the angle-time curve of each joint and the position-time curve of handle under setting rehabilitation path by using Solid Works software. Experimental results showed that the rationality with the central-driven structure design had been verified by the fact that the handle could move under setting rehabilitation path. The effectiveness of kinematics equations had been proved, and the error was less than 3° by comparing the angle-time curves obtained from calculation with those from motion simulation.
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Humans , Biomechanical Phenomena , Models, Biological , Robotics , Stroke Rehabilitation , Upper ExtremityABSTRACT
BACKGROUND:Colagen materials have good biocompatibility and biodegradability, but also had some problems such as low mechanical strength, poor resistance to degradation exposed in the process of clinical application. Numerous studies have reported that proper crosslinking could improve the disadvantage of colagen materials, regulate porous network structure, sweling and degradation of colagen materials. OBJECTIVE: To optimize carbodimide crosslinking process of colagen sponge and determine the best process conditions. METHODS:Colagen sponge was cross-linked by carbodimide for the preparation of loose and porous colagen sponge. Meanwhile, we optimized the conditions of cross-linking, in which the selected concentration of carbodimide was 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 mmol/L, linking time was 2, 4, 6, 8, 12, 16, 20, 24 hours, and linking temperature was 5, 10, 15, 20, 25, 30, 35℃. We evaluated the best process conditions of colagen sponge through the aperture, porosity, water absorption, and degradation rate. RESULTS AND CONCLUSION:The optimal conditions were carbodimide concentration 50 mmol/L, crosslinking temperature 20℃,crosslinking time 6 hours. At this point, the average pore diameter of colagen sponge was 105 μm, the porosity was 79.45%, water absorption was 287.14%, and the degradation rate was 15.04% (2 days). The crosslinking of colagen sponge significantly improved its water absorption and degradation resistance.
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@# In this paper, the classification of the upper limb rehabilitation robot was discussed and the research progress was overviewed.Finally, the prospects of upper limb rehabilitation robot were put forward.